Responsive modelling of the mpox epidemic in England as a cross-government and academia collaboration: the process, challenges, and lessons learned
Authors: Jasmina Panovska-Griffiths, Nicholas A Watkins, Fergus Cumming, Luke Hounsome, Andre Charlett, Xu-Sheng Zhang, Thomas Finnie, Thomas Ward, Meera Chand, Johanna Hutchinson
Journal: The Lancet Microbe (2023)

On May 7, 2022, mpox (formerly known as monkeypox) was detected in a traveller returning to the UK from Nigeria. Before this outbreak, the UK had three mpox cases in September, 2018, with the index case also from Nigeria,1Petersen E Abubakar I Ihekweazu C et al.Monkeypox—enhancing public health preparedness for an emerging lethal human zoonotic epidemic threat in the wake of the smallpox post-eradication era.Int J Infect Dis. 2019; 78: 78-84Summary Full Text Full Text PDF PubMed Scopus (96) Google Scholar and apart from a presumed fomite transmission, no known transmissions from person to person were observed in the 2018 outbreak. For the 2022 outbreak, after the initial case, the number of reported mpox cases continued to increase over May, June, and early July, 2022, before declining throughout August and September, 2022. Over the course of this epidemic the majority of transmission has been within a defined subpopulation of gay, bisexual, and men who have sex with men (GBMSM) connected by sexual networks with no evidence of sustained transmission outside of these networks.2UK Health Security AgencyInvestigation into monkeypox outbreak in England: technical briefing 8.https://www.gov.uk/government/publications/monkeypox-outbreak-technical-briefings/investigation-into-monkeypox-outbreak-in-england-technical-briefing-8Date: 2022Date accessed: April 20, 2023Google Scholar As of Sept 16, 2022, there were 3412 laboratory-detected cases of mpox in England,3UK Health Security AgencyMonkeypox outbreak: epidemiological overview.https://www.gov.uk/government/publications/monkeypox-outbreak-epidemiological-overview/monkeypox-outbreak-epidemiological-overview-13-september-2022Date: 13 September 2022Date accessed: April 20, 2023Google Scholar with surveillance data available for about 1050 (31%) of 3412 and of the 3390 cases of known sex, 99% were men, and only 45 were women (all of them transgender) with 2359 cases in England known to be London residents (69%) of 3399 with reported home address. From the onset of mpox in May, 2022, the UK Health Security Agency (UKHSA) coordinated the public health response to the outbreak, which included public awareness of the symptoms and transmission routes; test–trace–isolate strategies aiming to identify cases, including through case finding and contact tracing, clinical management, and recommended isolation for positive cases and provision of supportive care; genomic sequencing to identify the viral clade(s); and a control programme of large-scale vaccination for mpox in GBMSM deemed at risk and additional smaller-scale vaccination of their contacts, health-care workers, and occupational exposure groups.4UK Public Health AgenciesPrinciples for monkeypox control in the UK: 4 nations consensus statement.https://www.gov.uk/government/publications/principles-for-monkeypox-control-in-the-uk-4-nations-consensus-statement/principles-for-monkeypox-control-in-the-uk-4-nations-consensus-statementDate: 2022Date accessed: April 20, 2023Google Scholar An integral part of the public response was the collation of relevant data from mpox cases and exposed individuals.2UK Health Security AgencyInvestigation into monkeypox outbreak in England: technical briefing 8.https://www.gov.uk/government/publications/monkeypox-outbreak-technical-briefings/investigation-into-monkeypox-outbreak-in-england-technical-briefing-8Date: 2022Date accessed: April 20, 2023Google Scholar The collated data included mpox testing results from people testing positive since May 6, 2022, comprising demographic, symptom onset date and types of symptoms, and epidemiological and exposure information. Mathematical modelling played an important role during the COVID-19 epidemic in England, providing scientific evidence to policy makers at important policy junctions. In early 2021, a formal collaboration between the Department of Health and Social Care advisory committee on pandemic modelling (Scientific Pandemic Influenza Group on Modelling—Operational) and the UKHSA Epidemiological Ensemble group was established. This hub provided weekly epidemic estimates5Park J Bevan L Sanchez-Marroquin A et al.Combining models to generate a consensus effective reproduction number R for the COVID-19 epidemic status in England.medRxiv. 2023; (published online Mar 1.) (preprint).https://doi.org/10.1101/2023.02.27.23286501Google Scholar and possible epidemic trajectories6UK Health Security AgencyEMRG medium-term projections for COVID-19 hospitalisations and deaths.https://www.gov.uk/government/publications/consensus-statements-on-covid-19/emrg-medium-term-projections-for-covid-19-hospitalisations-and-deaths-28-september-2022Date accessed: April 19, 2023Google Scholar as consensus estimates. Learning from this experience, in early May, 2022, the UKHSA Senior Modelling Leadership team established an mpox modelling consortium comprising government and academic epidemiological modellers working collaboratively to better understand and interpret the available data and use it to inform statistical and mechanistic models to predict future epidemic behaviour. The purpose of this consortium was to understand the transmission routes, identify early warnings of transmission outside GBMSM, evaluate the effect of different interventions and provide scientific evidence on estimates of current and future trends of the mpox epidemic in England. Members of the consortium had access to the available data collated into an anonymised line list managed by the UKHSA Data and Epidemiology Cell. Over the course of the response, consortium members addressed a series of research questions, based on the groups' expertise, skillsets, and interests. For example, modelling in the early stages of the mpox epidemic suggested that sustained growth of mpox among GBMSM was best explained by those individuals in sexual networks with large numbers of sexual partners.7Endo A Murayama H Abbott S et al.Heavy-tailed sexual contact networks and monkeypox epidemiology in the global outbreak, 2022.Science. 2022; 378: 90-94Crossref PubMed Scopus (16) Google Scholar Presymptomatic transmission was also noted as an important contribution to sustained mpox transmission as the epidemic continued.8Ward T Christie R Paton RS Cumming F Overton CE Transmission dynamics of monkeypox in the United Kingdom: contact tracing study.BMJ. 2022; 379e073153Google Scholar When cases started to decline from early July, 2022, modelling studies found different, but complementing causes for this decline. Behaviour change and vaccination were both found to be important control measures,9Brand S Cavallaro M Cumming F et al.The role of vaccination and public awareness in forecasts of monkeypox incidence in the United Kingdom.Research Square. 2022; (published online Oct 14.) (preprint).https://doi.org/10.21203/rs.3.rs-2162921/v1Google Scholar with modelling suggesting that vaccination against mpox in England was likely to have substantially reduced the numbers of new cases of monkeypox virus in GBMSM.9Brand S Cavallaro M Cumming F et al.The role of vaccination and public awareness in forecasts of monkeypox incidence in the United Kingdom.Research Square. 2022; (published online Oct 14.) (preprint).https://doi.org/10.21203/rs.3.rs-2162921/v1Google Scholar Although not measured directly, changes in sexual behaviour were also explored as a possible explanation of the decline in mpox cases from the middle of July, with reduced sexual behaviour in GBMSM identified as a credible potential reason (Zhang X-S and colleagues, submitted).9Brand S Cavallaro M Cumming F et al.The role of vaccination and public awareness in forecasts of monkeypox incidence in the United Kingdom.Research Square. 2022; (published online Oct 14.) (preprint).https://doi.org/10.21203/rs.3.rs-2162921/v1Google Scholar Finally, delays between symptom onset and health-care presentation were also studied as a possible cause for the change in growth rate of mpox over the May–August period, with modelling suggesting that the delay in reporting to health care with symptomatic mpox declined from an average of 20 days in early May, 2022 to around 7 days in August, 2022.10Panovska-Griffiths J Hinch R Park J et al.Slowly declining growth rates and dynamic reporting delays characterise the Monkeypox epidemic in the UK over May–August 2022.Research Square. 2022; (Published online Nov 23.) (preprint).https://doi.org/10.21203/rs.3.rs-2298855/v1Google Scholar Coordination of these modelling activities was achieved via weekly meetings in which analyses were shared, emerging, current, and urgent questions were discussed, and modelling work was divided up across different streams and modelling teams. Details of the separate modelling streams were published as part of the consensus statements that UKHSA produced throughout the response.11UKHSA Mpox technical briefings.https://www.gov.uk/government/publications/monkeypox-outbreak-technical-briefingsDate accessed: April 20, 2023Google Scholar This process of coordinating, allocating, and using these mpox modelling analyses to inform policy showed the strength of collaborating across both government and academia. First, the anonymised data were available in near real time, refreshed on a weekly basis to all consortium members. The modelling groups were invited to carry out analysis that best suited their interests and skillsets. This supported an approach in which individual expertise was combined in a synergistic way, making the best use of available knowledge and skills. Second, the approach to analysing the data was cross-disciplinary and heterogeneous with the portfolio of work comprising various models: from Bayesian inference, via stochastic susceptible-exposed-infectious-recovered dynamic models to large-scale network models. In this aspect, the weekly meetings were regularly attended by cross-disciplinary modelling experts, with informative discussion across data, modelled results, and interpretation of those results. A consensus statement was collated as a result of the modelling consortium meetings, with different modelling streams represented, and published on the UKHSA website.11UKHSA Mpox technical briefings.https://www.gov.uk/government/publications/monkeypox-outbreak-technical-briefingsDate accessed: April 20, 2023Google Scholar This made the process open and transparent. Third, the modelling results were shared in a timely and responsive way. Following the principle that "an 80% right paper before a policy decision is made is worth ten 95% right papers afterwards",12Whitty CJM What makes an academic paper useful for health policy?.BMC Med. 2015; 13: 301Crossref PubMed Scopus (102) Google Scholar the consortium collectively produced and openly published on the UKHSA website a collection of complementary and quick analyses useful for timely policy advice. Finally, the weekly consensus statement comprised analysis from multiple independent models. As Bates and Granger noted in their seminal paper from 1969,13Bates JM Granger CWJ The combination of forecasts.J Oper Res Soc. 1969; 20: 451-468Crossref Google Scholar an average of two predictions is more accurate than one alone, so by combining several independent analyses we were better able to capture the uncertainties in the modelling projections. Additionally, use of a set of models and analysis allowed a more robust and multi-dimensional response to the epidemic. Learning from the mpox consortium modelling experience and in preparation for the next pandemic, we identified three areas for improvement: rapid access to data for modellers early in the epidemic, efficient processes of working across the different modelling streams, and more transparent quantification of the uncertainty from the modelling predictions. On the first point, data availability and the process of sharing anonymised data with modelling groups in an effective and continual way was challenging during the early phases of the mpox epidemic. High quality, pertinent data is a prerequisite for modelling and having the right data available in a timely manner is crucial early in an outbreak. During the early stages of the epidemic in the UK, the quality and availability of data was scarce, particularly in the identification of infector–infectee pairs, restricting the contributions that could be made. The inability to link data in real time limited the ability to assess control measures directly, in particular, vaccine effectiveness. Future responses need to carefully consider the essential data required to inform on the epidemiology of incident and assessment of control measures and facilitate access as early as possible. For the mpox response, access to anonymised data was made available to modelling groups with existing access to UKHSA controlled systems. We are developing approaches, in line with relevant legal requirements, which will support wider access in the future. On the second point, although there was an effective streamlining process within the weekly meetings to formulate working groups to answer different modelling needs, there were some challenges associated with this. For example, although the collaboration with the Joint Universities Pandemic and Epidemiological Research (JUNIPER) consortium has been very fruitful, culminating in a productive UKHSA–Juniper meeting held in August, 2022, expansion of the expertise to other groups would further strengthen the approach. There will, however, remain the need to balance speed with inclusivity. Finally, a crucial aspect in modelling, and specifically in early outbreaks, is accounting for and communicating the uncertainties emerging from the modelling results. These can include uncertainty around specific behaviours and degrees of risk for individuals. For example, there was little detailed historical data available on the sexual networks in the affected population. Work to understand how to account for these uncertainties within different models requires work outside of the epidemic. In summary, the mpox modelling consortium that UKHSA coordinated as part of the mpox response has illustrated how effective cross-government and academic collaboration can offer timely, responsive, interdisciplinary, and informative modelling for public health advice during an emerging outbreak. The consortium were able to analyse and model the data in real time, effectively tracking the status of the epidemic and offering timely and responsive informative advice to public health authorities on several emerging and imminent questions around mpox transmission. We acknowledge members of the Juniper consortium alongside Steven Riley (UKHSA), Thomas House (University of Manchester), Eric Voltz, Peter White, Neil Ferguson (Imperial College London), Peter Vickerman (University of Bristol), Matt Keeling (University of Warwick), Robert Hinch, and Christophe Fraser (University of Oxford) for insightful ongoing discussions and input to the responsive mpox modelling work. JP-G's work was supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care. The funders had no role in the study design, data analysis, data interpretation, or writing of the report. The views expressed in this article are those of the authors and not necessarily those of the UK Health Security Agency or the UK Department of Health and Social Care.